Measurement instruments are often used to measure transient or intermittent signals that occur rarely and at unpredictable times. It is often useful to make multiple independent measurements on such signals using different measurement parameters to obtain different perspectives. The various measurement parameters that must be specified to run a measurement on a measurement instrument shall hereinafter be collectively referred to as a “measurement setup”. Current measurement instruments (including spectrum analyzers, oscilloscopes, network analyzers, logic analyzers, etc.) allow a user to enter only a single measurement setup at a time. The user must wait for a desired signal to occur and a measurement of the desired signal to be made, before entering a new measurement setup into the instrument again to make a subsequent measurement. However, if the desired signal is unpredictable or infrequent, the user may not be present after a measurement occurs to enter a new measurement setup, and may miss other occurrences of the desired signal. Even if the user is present, the input process wastes valuable time during which other occurrences of the signal may not be captured as a result.
A user enters a measurement setup by providing the measurement instrument with parameters such as what trigger event to look for, how much data to collect before the trigger event, how much data to store after the trigger event, which sample rate or bandwidth to use, etc. Current measurement instruments only make a single measurement based on a single measurement setup using a single section of memory. Sometimes these single measurements are the result of multiple data collections averaged together, but what has been lacking is the ability to make multiple independent measurements all entered by the user at one time, and to be able to independently recall and analyze all the data from those measurements afterwards.
FIG. 1 shows a simplified block diagram for a typical prior art measurement instrument 10. A central processing unit (CPU) 11 controls data acquisition circuitry 15, a direct memory access (DMA) controller 16, and trigger circuitry 17 to acquire data from an input signal 12 according to a measurement setup 14 that is entered by a user. Entering the measurement setup 14 includes programming parameters such as the trigger event, the amount of data to be captured before and after the trigger event, the center frequency and gain for the signal, the measurement bandwidth, the sample rate, etc. The input signal 12 is applied to the data acquisition circuitry 15, while other trigger signals 13 are applied to the trigger circuitry 17. A trigger event may consist of either the occurrence of an attribute of the input signal 12 or an occurrence of one or more trigger signals 13 as determined by the measurement setup 14.
The CPU 11 controls the DMA controller 16 to begin storing pre-trigger data in the memory 18 in a circular fashion. When the number of pre-trigger points specified in the measurement setup 14 have been captured, the CPU 11 or DMA controller 16 arms the trigger circuitry 17 and data acquisition circuitry 15 to monitor the input signal 12 and trigger signals 13 to check for the trigger event. If no pre-trigger points are required, the trigger circuitry 17 and data acquisition circuitry 15 are armed prior to the capture of the first point. Once the trigger event is detected, the DMA controller 16 stores the trigger point and the post-trigger data captured according to the measurement setup 14 into the memory 18. The data acquisition circuitry 15 may also do signal processing such as filtering or decimation on the acquired input signal 12 as determined by the measurement setup 14, before forwarding the data to the DMA controller 16.
FIG. 2 shows an exploded view of the memory 18 in FIG. 1. Memory 18 is typically random access memory (RAM) but may be any circularly writable storage medium able to keep up with the sampled data. The memory 18 is typically configured as a circular buffer—as indicated by the arrow 20, the DMA controller 16 writes data to the memory 18 from beginning to end. When the DMA controller 16 reaches the end of the memory 18, it loops back to the beginning to write anew. Wrapping back to the beginning to write anew includes writing over any previously stored data in the memory 18.
Even before the trigger event occurs, the DMA controller 16 stores measurement data acquired from the input signal 12 into the memory 18. This measurement data is categorized as “pre-trigger” data in FIG. 2. The DMA controller 16 will store pre-trigger data and loop as needed, repeatedly, until the user-specified trigger event occurs. Once the trigger event occurs (shown as “trigger” in FIG. 2), additional measurement data (“post-trigger” in FIG. 2) is stored according to the measurement setup 14 until the specified amount of data has been captured and the measurement ends. No more data is taken until another measurement setup 14 is entered. The DMA controller 16 saves the memory address at which the trigger has been stored. This is used later by the CPU 11 to interpret the contents of the memory 18. The combined number of pre-trigger and post-trigger points plus one (for the trigger point itself) should be less than or equal to the size of the memory 18.
The prior art instrument in FIG. 1 is only capable of making a single measurement based on a single measurement setup 14. Some prior art instruments are capable of averaging, histogramming, or gating sampled data from multiple triggers and multiple data acquisitions into a single measurement result. However, the sampled data associated with each acquisition is not individually saved for independent analysis, and the measurement parameters for each acquisition within the measurement are identical.
In some prior art configurations, an external computer is used with the measurement instrument to make multiple independent measurements. In these cases the external computer must copy measurement data out of the memory of the measurement instrument, and then reprogram the instrument for the next measurement. This process, though automated, takes time and potentially results in a loss of measurement opportunities.
Therefore, there remains a need for a measurement instrument that can make multiple independent measurements from multiple measurement setups that are entered at a single time, and can store all of the acquired measurement data in its own memory space.